Kenneth Peterson, PhD, is a professor in KUMC’s Department of Biochemistry and Molecular Biology.

A group of geneticists are arguing for a change in the way scientists think about one of the most sacred tools of the trade: the published paper.

An editorial in this month's Nature Genetics, titled "Crowdsourcing human mutations," suggests that researchers begin putting less emphasis on scientific papers and more emphasis on contributions to databases that scientists can mine for new theories. They argue for "microattribution" — published credit for small bits of new information that would normally never make it into a peer-reviewed journal article.

"A lot of data doesn't get published because it doesn't rise to the significance of a paper," says Kenneth Peterson, PhD, a professor in the University of Kansas Medical Center's Department of Biochemistry and Molecular Biology. "But investigators are still interested in how to make it useful."

Peterson's lab was instrumental in proving how it could work.

Among other things, Peterson studies the genetic causes of red blood cell diseases including sickle cell disease and thalassemias, as well as polycystic kidney disease. From his research and reading of scientific journals, Peterson knew that one way of potentially fighting the blood diseases is to activate fetal globin genes, whose protein products are only found in the fetus.

At the same time, a group of researchers led by George Patrinos, an assistant professor of pharmacogenetics at the School of Health Sciences at the University of Patras in Greece, was recognizing that, since the completion of the human genome project, scientists needed a better way to keep track of vast numbers of genes and their mutations.

"It has become increasingly difficult to report small numbers of human variants in scientific journals," Patrinos would later write.

The problem seemed to be the scientific journal itself, that long-hallowed medium in which scientists report their discoveries and inspire other scientists to think up new hypotheses.

To solve the problem, Patrinos and his colleagues tested their theory of microattribution — giving scientists published citations for the small but important discoveries that they contributed to a database.

Patrinos and his colleagues created a database of 1,941 genetic hemoglobin variants in 37 genes, making sure that everyone who contributed to the database got citations.

That's where Peterson entered the picture.

"If you generate an all-encompassing database of genetic mutations, you can use it to predict new or undiscovered genetic mutations that cause disease," Peterson explains. In this case, he says, someone working with the database had predicted that a simple mutation would activate the sickle-cell-disease-fighting fetal globin gene in an adult.

The scientist had used the database to predict what Peterson's lab was already doing. Using an animal model, Peterson was able to activate the fetal gene via the predicted mutation in an adult mouse. "That was an important discovery if you're looking for things that can turn genes on or off," Peterson explains. "Once you make those discoveries, you can create drugs that will target the proteins that turn on those genes."

Researchers just have to know where to look for mutations they won't read about in journal articles.

According to the Nature Genetics editors, Patrinos, Peterson and their 43 co-authors have shown that "a process of community annotation of rare and common variants influencing hemoglobin levels can bring unpublished variants into the public domain."

Finding new ideas to test through microattribution is, Peterson says, "applicable to a lot of genetic diseases. Eventually there may be similar databases for cystic fibrosis, Alzhiemer's disease, polycystic kidney disease and muscular dystrophy, just to name a few."

All of which could result in scientists rethinking how they define what's important when it comes to scientific publications.